技术 - JuicyScore 博客

可靠的合作伙伴和技术创新的引入有助于金融科技公司在市场上的增长变得更加稳健。国际金融科技公司 与风险管理和反欺诈解决方案市场领先企业JuicyScore合作已经超过8年了，最近还评价了其新产品JuicyID，该产品有助于降低二次贷款的运营和信用风险。

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Reliable partners and technological innovations help fintech companies grow in the market with confidence. During more than 8 years of successful cooperation with JuicyScore, which is the market leader in risk management and anti-fraud solutions, the international Fintech group [UnaFinancial](https://una.financial), has recently evaluated a new product – JuicyID. It was designed to reduce operational and credit risks in secondary loans. 

## What challenges did UnaFinancial Face?

Mikhail Koromyslov, the Group's Anti-Fraud Director, shared his opinion about the product: “We needed a reliable partner able to deliver alternative data across all the markets of our presence. The JuicyScore team provided the technology that meets our anti-fraud needs. From now on, the JuicyID solution is a part of our comprehensive anti-fraud architecture.”

## What Results have been achieved with JuicyID?

UnaFinancial’s Anti-Fraud Director Mikhail Koromyslov said: “Judging by the primary results after the pilot launch, we managed to develop a set of comprehensive markers and variables that enriched our company’s anti-fraud model in the Philippines. It helped to reduce the risk level in the early re-loan portfolio by several percentage points.”

From the list of around 20 markers, the main attention was drawn to new variables able to detect signs of high-risk behavior. They may include the use of untypical foreign languages on the device, missed fingerprints, various risky virtual machines, and combinations of aggregated IDX index variables.

## What risk- and stop-marker rules did UnaFinancial use?

“We applied a dozen of rules together with stop and risk markers. I would particularly like to mention individual scoring: it shows good potential for identifying high-risk segments on repeated loans, mainly the early ones. We can identify segments of a few percent size with risk levels beyond the product P&L in this particular category.

Stop markers to detect virtual machines and browser anomalies turned out to be a distinctive feature of the solution. 

Besides, IDX-type indexes or variables showed very good results, especially taking into account that the JuicyScore team created custom indexes for us. They involved an updated aggregate index based on IDX3 - DeviceMarkers and other device anomalies, as well as secondary risk markers that allow us to increase stability and improve the overall application efficiency.”

## A detailed introduction to the JuicyID Solution

The Device ID returning responses are the most stable and consistent digital fingerprint on the market. It comes with a built-in data vector featuring 100+ attributes. It makes it possible to build different rules to prevent the risk of fraud and unfair virtual user actions as well as establish a balance between ROI and cost, given that preventing fraud risk in the online channel is one of the major business challenges today.

Stop-markers will allow us to identify the app segment with high fraud risk at the early stages of application filtering. JuicyID vector variables will help mitigate the level of social fraud risk within the flow. IDX1 – IDX4 indices can be used to build credit scoring models for applications that have successfully passed all stages of pre-filtering. These models help to identify both high-default risk segments for automatic screening and low-risk segments for increasing the approval rate.
What’s more, JuicyID is an effective solution for safeguarding user accounts, especially if the physical user is not tied to a single virtual one. JuicyID serves greatly for detecting multi-accounting fraud, as well as identifying users with multiple sets of personal data utilized for fraudulent purposes. JuicyID comes as an ultimate solution for products with instant response requirements.   

## About UnaFinancial

UnaFinancial is a group of companies developing easy-to-use digital financial solutions in the Middle East, Asia, and Europe. The group aims to provide simple and reliable access to finance through innovative technologies, focusing on what customers truly need. Since its foundation, UnaFinancial has served more than 14 million clients, who got access to over 1.5 bn USD worth of loans.


Reliable partners and technological innovations help Fintech companies grow in the market with confidence. During more than 8 years of successful cooperation with JuicyScore the international Fintech group UnaFinancial has recently evaluated a new product – JuicyID. It was designed to reduce operational and credit risks in secondary loans. 


UnaFinancial: JuicyID helped to reduce operational risks in the Philippines

UnaFinancial: JuicyID使得在菲律宾的运营风险得以降低

对于那些在组建风险管理团队方面遇到困难的客户，我们开发了一款新工具叫JuicyScoreAI。该工具旨在自动化定制反欺诈评分模型的构建过程和最优变量的选择。

Juicy_AI_final.png

It is often difficult for online companies to build an in-house team that not only keeps an eye on all trends in digital risk management but also applies them effectively to the company’s benefit. It becomes particularly challenging in an environment of ever-changing technology and evolving market trends, where you need to stay up-to-date with the latest innovations to be ready to adapt quickly.

For those of our clients who face difficulties in building risk management teams, we have developed JuicyScoreAI. It is a brand-new tool designed to automate the process of building custom anti-fraud scoring and selecting optimal variables. It delivers a blend of powerful analytical capabilities with an intuitive user interface, making it easy and accessible for both novice users and experienced data experts.

## What Is JuicyScoreAI?

JuicyScoreAI's primary goal is to facilitate the efficient machine learning models’ development and deployment. The tool automates crucial steps such as data analysis and variable selection. It helps financial organizations optimize their predictive modeling efforts. It ensures more accurate estimates and leads to excellent results. Those who need rapid iteration and validation of models, allowing users to adapt to new data or changing conditions quickly, will find JuicyScoreAI extremely useful.

In simpler words, the product contains online functionality to automate custom anti fraud scoring based on the JuicyScore infrastructure. It serves to increase the general value of JuicyScore. Besides, it can be useful in case of difficulties with creating your custom antifraud model based on your existing online business infrastructure.

## Who Can Benefit from Using JuicyScoreAI?

JuicyScoreAI was designed to meet the needs of a wide range of users. It may turn out to be an effective instrument for data analysts who need to perform rapid exploratory data analysis as well as experienced data scientists developing robust predictive models.

By integrating with existing data workflows, JuicyScoreAI will become a crucial element in any organization that relies on data-driven decision-making. For example, the finance industry relies on data drastically. JuicyScoreAI enhances the ability to extract valuable information from complex data sets. The product will help risk professionals establish simpler and faster approaches to building custom models.

## JuicyScoreAI Key Features

- **Data Preparation**: Users can upload their datasets directly into the tool. JuicyScoreAI supports multiple data formats and ensures that the data integrity is maintained from upload through analysis.
- **Data Analysis**: The tool automatically performs statistical analysis on the provided data, calculating essential metrics like the Gini coefficient, KS statistic, Information Value (IV), and p-values. This analysis helps users identify the most predictive variables and understand the statistical significance of their data.
- **Model Development**: JuicyScoreAI offers flexible model development options, including Generalized Linear Models (GLM), Decision Trees, and Gradient Boosting. Users can select the most appropriate modeling technique based on the analysis results and tailor their approach to fit specific business needs.

Moreover, the JuicyScoreAI solution helps users quickly identify the most business-relevant variables to boost business growth. The tool can be used to compare different AI methods for assessing fraud risk and involve JuicyScore experts in consulting on ways to build custom models.

## How JuicyScoreAI Works?

We should note that JuicyScoreAI is a complimentary product. It comes as an add-on to the already installed JuicyScore solution. An expert, responsible for risks in online business, uploads the data based on flags: a list of sessions with exposed fraudulence values for individual sessions/applications. Based on the uploaded file, JuicyScoreAI generates answers based on 10 variables or so-called IDX-indexes. Aggregated IDX variables represent a set of rare events and factors of the same nature. They are collected with the help of Deep Machine Learning algorithms forming a single variable. Later on, this variable can be used for either modeling or embedding into the decision-making system of credit organizations.

All IDX indexes were created as Gaussian variables. We did it for several reasons. First, they are subjected to statistical significance assessment/validation (meaning a classical p level of significance). Secondly, they allow us to structure the entire probability space depending on the type of fraud events. You may find more valuable insights and details on indexes in our article about [rare event risk assessment](https://juicyscore.ai/en/blog/rare-events-risk-assessment-how-data-science-can-help-business-to-thrive-en). The scoring response is based on those indexes.

![Model Development (1).png](/uploads/Model_Development_1_14da76cc2c.png)

Building a model: an expert can select the most appropriate indexes and machine learning algorithm used to build a specific model.

Based on the 10 indexes, we get a distribution of the predictive power of each index. The main JuicyScoreAI advantage is the ability to operate client data and train on current sessions in real-time.

This is how we can pull out the benefits of index informativeness from genericScore (API v15), which represents a set of models built on IDX1-IDX10 aggregates and many auxiliary variables. The data collected during the JuicyScore or JuicyID operation is a basis. Then, the data is used to build a model. Although it is not generic or basic, it perfectly suits specific business cases. In this way, the expert has a variety of tools for model management. He gets a more basic and generic model that fits all. Besides, the model is based on company data, which makes scoring more accurate and precise.

![Data Analysis (1).png](/uploads/Data_Analysis_1_21a70d1f4b.png)

Every time an expert uploads his session data, he can overview three main metrics to assess the informativeness of the variable that can be used in a model.

The statistical index p_value is used to decipher the results of hypothesis tests. If the p_value is less than 5%, this variable is statistically significant to the target variable (predicting fraudulence session). In essence, a p_value of less than 5% recommends that this index should be added to the custom model. The criteria for incremental gini value and significance in ks statistics should be considered separately.

The IV for each index is calculated in the model information section. You can find recommendations on the most suitable indexes for forming a custom model in the personal account.

## What Types of Data-Based Models Can be Built?

1. Generalised Linear Model. The formula can include various borrower-related data types (except for personal data). This includes some previously issued loans and estimated disposable income. However, the generalized linear model can handle more complex types of data, unlike the simple linear model.
2. Decision Tree. Using a decision tree helps the team to assess existing risks as quickly as possible. Simplicity and visibility are the main advantages of this model.
3. Gradient boosting. This model works well when risk professionals work together. It relies on a baseline forecast taking into account all subsequent steps and iterations of correcting and improving the forecast. It results in more accurate forecasts.

After selecting the model build type, a risk expert receives a model metric. The customization can vary depending on the business objectives. For example, if a lender needs tighter tuning and filters to exclude more applications for a safer strategy, which in particular may be required during seasonal fraud for example, during the upcoming holidays), a risk manager can configure a custom model that rejects as many borrowers with risk markers above the sample average as possible.

An expert can also customize the model with a milder rejection policy mode to increase the approval rate of applications. The JuicyScoreAI solution helps to set up an optimal model that will both increase the approval rate and also track the flow of risky applications. In addition, each model can be trained. It uses 60% of the data sampling for training and 40% for hypothesis testing and validation.

Each JuicyScoreAI feature is designed to streamline the process from data preparation to model deployment. By understanding and utilizing these features, users can enhance their predictive modeling capabilities and effectively make data-driven decisions. JuicyScoreAI supports several common data formats and provides detailed statistics for decision-making when building a model. We are convinced that our new product will be useful for online companies. It will help to strengthen their position in the modern digital landscape significantly.

For those of our clients who face difficulties in building risk management teams, we have developed JuicyScoreAI. It is a brand-new tool designed to automate the process of building custom anti-fraud scoring and selecting optimal variables.

Optimizing custom anti-fraud models with JuicyScoreAI

自动化定制反欺诈模型：JuicyScoreAI

随着技术世界不断发展，10多年以前出现的双重认证（2FA）或多重要素验证(MFA)得到广泛应用。 使用双重认证（2FA）或多重要素验证(MFA)已经成为常态。 
广泛采用基于双重认证（2FA）的解决方案显著降低了欺诈风险，并更有效地抵御数字环境中的欺诈攻击。

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We can’t but agree that technological world is constantly evolving. Relatively recent widespread use of two-factor authentication (2FA) or multi-factor authentication (MFA), which became widely used about 10 years ago, has become commonplace. The widespread use of 2FA-based solutions has resulted in a significant reduction in fraud risks and a more effective response to fraud attacks in the digital environment. If you are reading this article and planning to implement 2FA-based solutions in your online business, we can definitely say that this step will bring significant benefits to you and your customers.

Online scammers are constantly developing new methods to get their hands on customers' personal information. For this very reason it is becoming glaringly obvious for many online businesses that implementing two-factor authentication solutions is becoming an integral part of improving the security of systems and user accounts. Two-factor authentication provides an additional layer of security for gaining access to a website, application or resource by ensuring the user's identity is verified through two different factors, such as a password and a one-time code received via SMS or application. This helps to prevent unauthorized access to accounts and protects customers' valuable personal information from online scammers.

The article will be extremely useful for those who have long mastered 2FA/MFA-based solutions. Unfortunately, online scammers are constantly developing new methods to bypass security systems, and 2FA/MFA systems are no exception. Over the past few years, we have been actively studying emerging risks both related to application fraud and problems of personal accounts protection. We have been facing the rise of a large number of new threats and attacks that have begun to emerge with the proliferation of 2FA-based security systems. What are these risks? We can divide them in a few groups:

- Technical fraud - synthetic accounts, [social engineering](https://juicyscore.ai/en/blog/remote-access-and-social-engineering-risks-prevention-best-practices-en), remote access, total account takeover and a number of other cases of fraud attacks;
- Social fraud - family fraud (for example, when a person applies for a loan on behalf of his or her relative), [multiple accounts](https://juicyscore.ai/en/blog/enhance-the-effectiveness-of-2fa-protect-your-customers-en) (multi-accounting), credit shopping and some other cases.

## What are the most effective approaches to counteract these risk groups? Here are the most common and most effective methods:

- Analysis of risk signals related to login or account use;
- Build a system for monitoring and reducing the number of duplicate or additional user accounts (if this is unnecessary to provide services to the client);
- Additional checks whether login/account usage details match with the previous user session, including device details and Internet connection;
- Apply rare events risk scoring of events and/or signals to identify the most risky sessions. This method is applicable in such cases, where the risk of material losses is involved (for example, credit card application online process or loan applications);
- Apply 3FA+ solutions as an additional verification tool in cases of above-average risk. Possible solutions: additional questions to the user on the information that should only be known to the account owner and preferably should not be associated with personal account details (for example, how many bank accounts this person has).

## JuicyScore high-risk variables and markers

Also it is sufficient to observe that JuicyScore high-risk variables and markers allow you to identify additional fraud segments in conjunction with 2FA tools.

- IDX1 Stop Markers - Combination of 50+ rare events with high risk of tech fraud;
- IDX2 User Behaviour Markers - Combination of behaviour markers, including application frequency, user behaviour parameters, etc.;
- IDX3 Device Markers - A combination of secondary device risk markers, including various device parameters and device anomalies;
- IDX4 Connection Markers - Combination of secondary risk factors, consists of various device markers and anomalies;
- Duplicating device - Repeated application from the same device within the minimum loan term according to the lender's account settings;
- Same device - Device matching with previous and current applications for associated devices and users;
- Total num of applications with browser hash in 1 hour (/ 1 / 7/ 30 days) - The total additional number of applications (for the current service subscriber or user) to a given user with the specified browser hash over the last 1 hour;
- Less tenor days - An indication of whether this application is repeated for a period shorter than the number of days specified in the previous application;
- Time on page - Duration of filling out a page , application form, etc.

##  What results can be achieved after implementing additional protection as part of 2FA?

Implementation of solutions based on JuicyID to enhance the protection of personal accounts not only reduces the risk of fraud, but also increases the economic efficiency of online businesses by reducing operational and credit losses.

JuicyID is a lightweight version of JuicyScore. The product is designed to protect accounts in online services. It's main feature is a high response speed.

The Device ID, which returns in the response, is one of the most stable and sustainable digital fingerprints on the market, it also has a data vector of 100 attributes, which allow you to build various rules for preventing the risk of fraud and spot shady behaviour of a virtual user, maintaining the balance of payback for investments at the same time.

Stop markers allow you to identify segments of high risk applications at early stages of applications filtering: JuicyID vector variables reduce the level of social fraud risk in the flow, while IDX1 - IDX4 indexes can be used to build credit scoring models for applications that have successfully passed all pre-filtration stages. These models help to identify segments with both - high risk of default for automatic filtering as well as low-risk segments in order to increase approval rates.

JuicyID is the optimal solution for protecting user personal accounts, especially if a physical user is not tied to one virtual personal account. JuicyID also can be of great use spotting cases of multi-accounting, as well as any cases of using multiple sets of personal data for shady purposes. 

This is just the first introductory article devoted to our research in the field of 2FA Solutions use for risk management purposes in general and account protection in particular. We will shred some light on other aspects of 2FA Solutions use in the future.

Relatively recent widespread use of two-factor authentication (2FA) or multi-factor authentication (MFA) has become commonplace for many online businesses. If you are reading this article and planning to implement 2FA-based solutions in your online business, we can definitely say that this step will bring significant benefits to you and your customers.

Enhance the effectiveness of 2FA: protect your customers

El mundo de la tecnología está en constante evolución y el uso relativamente reciente y generalizado de la autenticación de dos factores (2FA), que apareció hace poco más de 10 años, o la autenticación de múltiples factores (MFA), ya se ha vuelto familiar. El uso masivo de soluciones basadas en 2FA ha reducido significativamente los riesgos de fraude y ha sido más eficaz para resistir los ataques de fraude en el entorno digital. Si está leyendo este artículo y solo está pensando en implementar soluciones basadas en 2FA, podemos decir con seguridad que es muy probable que la implementación de una solución de ESTE tipo le beneficie a Usted y a Sus clientes de manera significativa.

Los estafadores en línea están desarrollando constantemente nuevos métodos para robar los datos personales de los clientes. Debido a esto, cada vez más empresas en línea están llegando a la conclusión de que la implementación de la autenticación de dos factores se está convirtiendo en una parte integral de la mejora de la seguridad de los sistemas y las cuentas de usuario. La autenticación de dos factores proporciona una capa adicional de seguridad para obtener acceso a un sitio web, aplicación o recurso, asegurando la verificación de la identidad del usuario a través de dos factores diferentes, como una contraseña y un código de un solo uso recibido a través de SMS o aplicación. Esto ayuda a prevenir el acceso no autorizado a las cuentas y protege los valiosos datos personales de los clientes de los estafadores en línea.

Escribimos este artículo principalmente para aquellos que ya dominan y utilizan activamente soluciones basadas en 2FA/MFA durante mucho tiempo.

Desafortunadamente, los estafadores en línea están desarrollando constantemente nuevos métodos para eludir los sistemas de seguridad y los sistemas 2FA/MFA no son una excepción. En los últimos años, hemos estado estudiando activamente los riesgos que surgen tanto en relación con el fraude de solicitud como con los problemas de protección de las oficinas personales. Nos enfrentamos a un número creciente de nuevas formas de amenazas y ataques, que comenzaron a manifestarse con la proliferación de sistemas de defensa basados en 2FA. 

_¿Cuáles son estos riesgos? Damos algunos grupos de ejemplos:_

- Fraude técnico-cuentas sintéticas, ingeniería social, acceso remoto, toma de cuenta total y una serie de otras formas de ataques de fraude;
- Fraude social: fraude familiar (por ejemplo, cuando una nieta toma un préstamo a nombre de su abuela), cuentas múltiples (multi-accounting), compras de crédito y otros tipos de fraude.

*¿Qué enfoques existen para contrarrestar estos grupos de riesgo? Aquí están las soluciones más comunes y más efectivas:*

- Análisis de señales de riesgo de Inicio de sesión o uso de la cuenta;
- Construir un sistema para monitorear y reducir el número de cuentas duplicadas o adicionales del usuario (si es innecesario para proporcionar servicios al cliente);
- Verificar si los detalles de Inicio de sesión/ uso de la cuenta coinciden con la sesión anterior del usuario, incluidos los detalles del dispositivo y la conexión a Internet;
- Introducción de eventos de Puntuación de riesgo y / o señales para identificar las sesiones más riesgosas en los casos en que se trata de un riesgo de pérdida material (por ejemplo, abrir una tarjeta de crédito en línea o tomar un préstamo);
- La introducción de 3FA+ como una herramienta de verificación adicional en caso de riesgo superior a la media. Qué soluciones son posibles: preguntas adicionales al usuario sobre lo que solo debe ser conocido por el titular de la cuenta y preferiblemente no debe estar relacionado con los detalles personales de la cuenta (por ejemplo, cuántas cuentas bancarias tiene una persona).

Además, cabe destacar los índices y marcadores de alto riesgo de JuicyScore, que permiten identificar segmentos de fraude adicionales junto con los instrumentos 2Fa.
- IDX1 Stop Markers-Combinación de más de 50 eventos raros con alta probabilidad de fraude a través de la manipulación técnica del dispositivo;
- IDX2 user Behaviour Markers-Combinación de marcadores de comportamiento, incluidas las respuestas de frecuencia y los parámetros de comportamiento en línea del usuario virtual;
- IDX3 device Markers-Combinación de marcadores de riesgo secundarios por dispositivo, incluye varios parámetros del dispositivo y anomalías por dispositivo;
- IDX4 Connection Markers-Combinación de parámetros de red y anomalías;
- Duplicating device - Solicitud repetida desde el mismo dispositivo durante el período mínimo del préstamo en la configuración de la cuenta del prestamista;
- Same device- Coincidencia del dispositivo de las solicitudes anteriores y actuales para dispositivos y usuarios relacionados;
- Total num of applications with browser hash in 1 hour (/ 1 / 7/ 30 days) - número total de solicitudes adicionales (para el suscriptor actual del Servicio) a este usuario con el hash del navegador especificado en las últimas 1 hora (1/7/30 días);
- Less tenor days-una indicación De si la solicitud se repite en un período inferior al número de días especificado en la solicitud anterior;
- Time on page-Cuabto tiempo tomo llenar la página con el formulario, etc.

*¿ Qué resultados se pueden lograr después de la implementación de la protección 2FA?*

La implementación de soluciones basadas en JuicyID para mejorar la protección de las cuentas personales no solo reduce los riesgos de fraude, también aumenta la rentabilidad de las empresas en línea al reducir las pérdidas operativas y crediticias.
JuicyID es una versión ligera de JuicyScore. El producto está diseñado para proteger las cuentas en los servicios en línea y se caracteriza por una alta velocidad de respuesta.

Device ID, la huella digital de dispositivos más estable y sostenible del mercado y un vector de 100 atributos, le permite construir diferentes reglas para prevenir el riesgo de fraude y acciones desleales del usuario virtual y mantener un equilibrio entre la recuperación y los costos, dado que la prevención del riesgo de fraude en el canal en línea es uno de los principales problemas comerciales hoy en día.
Los marcadores de parada identificarán el segmento de las solicitudes con riesgo de fraude y alto riesgo en las primeras etapas del filtrado de solicitudes: las variables del vector JuicyID reducirán el nivel de fraude de riesgo social en el flujo, los Índices IDX1 a IDX4 se pueden usar para construir modelos de calificación crediticia para solicitudes que hayan superado con éxito todas las etapas del filtrado previo. Estos modelos contribuyen a la asignación de segmentos de alto riesgo de incumplimiento para la deserción automática y segmentos de bajo riesgo para aumentar el nivel de aprobación.

JuicyID es la mejor solución para proteger las cuentas personales de los usuarios, especialmente si el usuario físico no está vinculado a una cuenta personal virtual. JuicyID también es excelente para ayudar a identificar casos de cuentas múltiples, así como para identificar cualquier caso de uso de múltiples conjuntos de datos personales con fines desleales. JuicyID también es ideal para productos donde hay un requisito de velocidad de respuesta.

Este es solo el primer artículo dedicado a nuestra investigación de gestión de riesgos sobre la protección de cuentas y cuentas personales utilizando 2FA. El próximo año abordaremos otros aspectos de los riesgos existentes.

El uso masivo de soluciones basadas en 2FA ha reducido significativamente los riesgos de fraude y ha sido más eficaz para resistir los ataques de fraude en el entorno digital.

Mayor eficiencia de 2FA para proteger a los clientes

加强双重认证（2FA）的效力以保护客户

全球数字化带来的不仅是机遇，也带来了风险，因为在线公司的数量增长，网上欺诈尝试的数量也随之增长。根据我们在数十个国家的运营经验，我们可以说，存在着一千多种不断完善的欺诈行为和模式。
与作为拒绝过滤器使用的常规风险标志不同，研究新的风险评估方法可以在打击在线欺诈方面取得更好的结果和增长。

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Along with the opportunities global digitalisation has brought us risks. The emerge of a large number of online businesses inevitably leads to a fraudulent traffic increase. Based on our experience in dozens of countries we can spot more than a thousand patterns of fraudulent behaviour, which, unfortunately, are constantly being improved by scammers. However we also believe that exploring the new methods of risk assessment gives much better result in terms of online fraud fighting than another superficial set of risk markers, which may be used as filters for automatic denial.

Today we are going to share our new methodology benefits, which allow online businesses to identify high-risk and carry out segmentation throughout the entire flow of applications. We are also proud to announce the launch of our new product: [automatic risk management reporting](https://juicyscore.ai/en/blog/risk-management-automatic-reporting-new-product-announcement-en), which will be available to all our clients in Q1 2023.

The aggregated results show a comparison of fintech companies in different regions of the world, data are given as of November of this year.

## The key methodology

Our methodology is based on the division of the entire session space into 4 groups, which are the following:

![](/uploads/Space_of_the_devices_En_001_2_5c76feaf6f.png)

The key positive factor of this approach is that all the high-risk sessions inevitably fall into one of the four groups, therefore, we can spot 100% of all possible online fraud attempts.

Another advantage is that this approach does not depend on the country, technologies, local legislation etc., which means that one can compare various online resources and countries.

![](/uploads/Fap_Sap_Hra_001_805b519f25.png)

Here you can see the share of FAP, SAP & HRA, which sums up the level of toxic / high-risk sessions by region.

## First Attempt Category

![](/uploads/FAP_Eng_001_0d1f7fffe3.png)


In the First attempt fraud category we included a combination of 50+ rare events with a high probability of fraud related to a device technical manipulation, in particular, the use of randomizers, some browser or operating system anomalies. We also noticed that the number of First attempt fraud in Latin America exceeded the same indicator in other regions almost two times, which may be an illustration of the increase of single fraudsters attacks in this region over the past month.

## Secondary Attempt Category

![](/uploads/SAP_En_001_df3d96d1a5.png)

In Secondary attempt fraud metric we included repeated devices as well as repeated users. We also noticed that the number of Second attempt fraud in South and South-East Asia and in Eastern Europe remains at a relatively high level, which indicates that fraudsters have been using large amount of data from the fraud net recently.

## High Risk Applications

![](/uploads/Hra_Eng_001_1_cce22acaac.png)

As you can see here, the level of high-risk applications in South Asia and Eastern Europe is the highest. Usually such figures occur in the countries with low income of the population and also may indicate the rise of a credit shopping in the region.

![](/uploads/Avg_device_Eng_001_c5bc02eb98.png)

The highest level of average inflow device quality has been spotted in the regions of South-East Asia and Eastern Europe. The lowest rate has been recorded in the countries of South Asia.

In this regard, we recommend online companies to take into account the following actions:

1. Fine-tune the process of regular reporting on key types of risk;
2. Give credence to preparation of strategies and risk policies for dealing with different situations. For example, if your company has a high FAP compared to the average in the region, then you should look for a wide range of stop factors for identifying this type of risk; if you have a low flow value in terms of device quality compared to the region, then it will be useful to reconsider the current customer acquisition strategy;
3. Make sure that the company has all the necessary technologies in order to detect the risk of fraud in real time - hundreds of fraudsters can attack the resource of a financial institution in a short period of time;
4. Check if the data information value is sufficient to improve the quality of models and decision-making systems;
5. Restrict the use of your users' personal data. Please note: often personal data is not required for auxiliary and vendor tasks - it is often possible to find an alternative solution based on anonymized sessions or tokens;
6. Determine for yourself a work option in case of a partial failure of the online infrastructure and a conservative work plan in case of a massive fraud attack (reducing the approval level for applications, introducing additional methods of user verification etc.);
7. Pay special attention to the user's behavior on your online resource in order to identify hidden correlations.

We are planning to create the system of consolidated reporting for all our clients in the nearest future.

Along with the opportunities global digitalisation has brought us risks. The emerge of a large number of online businesses inevitably leads to a fraudulent traffic increase. Based on our experience

Fraud traffic analysis in different regions: short study

不同地区的在线欺诈流量分析：研究

亲爱的朋友们和合作伙伴们！

能向大家介绍今年重要的事件，我们感到非常高兴！这是JS Platform。JS Platform是统一的平台，包含我们推出的一系列新产品。其中大部分已经开始推销世界各地。 

API-14.jpg

Dear friends and partners!

We are delighted to inform you about one of the most important events of this year: we have released a new set of products, combined into one platform: **JS Platform**. Most of the products are already available worldwide.

We challenged rather difficult task: to find and develop fundamentally new technologies, however this time we managed to outdo ourselves and released new generation of products, providing significant additional effect in comparison to the previous versions. For the last few months we managed to complete over 700 Data science, Risk management and IT tasks in order to release our new product.

## What is JS Platfor designed for? 

The new product generation has a range of significant changes from the perspective of efficiency for our partners. **Here are the main updates, which you will find in JS Platform**:

1. 15+ new parameters and variables in JuicyScore and JuicyID;
2. Antifraud scoring with Gini increase;
3. 45+ new anomalies and randomizers tests, which also let to detect various fraudulent digital instruments;
4. For the first time, a separate group of tests will be allocated for remote access detection on a user’s device;
5. The system of estimated income verification has been improved significantly for mobile SDK users;
6. We elaborated totally new approaches to self-learning models and their efficiency increase;
7. Offline to online solution has been developed. It helps to improve risk assessment significantly without affecting the conversion rate;
8. New device authentication technologies have been developed, including device randomization detection;
9. We created on-premise/local variant of JuicyBio, later on we are going to focus only on JuicyBio on-premise development. This solution is now undergoing the last stages of testing;
10. Service operating speed has been increased by 50%+

## What tasks the product manage to solve?

Despite the difficult situation all over the world as well as the essential changes in the work of all the financial market players, Juicy Team keeps up high development speed in order to extend the functionality of our products and generate more value to our clients and partners.

We permanently conduct researches to identify new attributes, work on strengthening of our expert valuation in [digital risk management](https://juicyscore.ai/en/blog/risk-management-automatic-reporting-new-product-announcement-en) to help our clients and partners in their day-to-day work, fraud prevention and risk assessment. Thanks to all of you for your support and sharing your ideas!

Yours, JuicyTeam

Dear friends and partners!  We are delighted to inform you about one of the most important events of this year: we have released a new set of products, combined into

JS Platform: 5 in 1. Risk management automation

JS Platform: 五合一。 风险管理自动化

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技术 - JuicyScore 博客

A collection of 5 posts

UnaFinancial: JuicyID使得在菲律宾的运营风险得以降低

自动化定制反欺诈模型：JuicyScoreAI

加强双重认证（2FA）的效力以保护客户

不同地区的在线欺诈流量分析：研究

JS Platform: 五合一。风险管理自动化

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技术 - JuicyScore 博客

A collection of 5 posts

UnaFinancial: JuicyID使得在菲律宾的运营风险得以降低

自动化定制反欺诈模型：JuicyScoreAI

加强双重认证（2FA）的效力以保护客户

不同地区的在线欺诈流量分析：研究

JS Platform: 五合一。 风险管理自动化

产品

规则

JS Platform: 五合一。风险管理自动化